Engineering Team Lead, Mistral AI
Managed Kubernetes
More information about location
Generative AI model developers
Be an early applicant
Generative AI model developers
501-1000 employees
Be an early applicant
More information about location
501-1000 employees
Company mission
To make frontier AI ubiquitous, and to provide tailor-made AI to all the builders.
Role
Who you are
- 2+ years of real people leadership. You have managed engineers — hired, coached, given honest feedback, and grown them. Hands-on contribution matters here, but this role is judged on the team you build and lead, not just the code you write
- You have shipped production systems in Go. Not dabbled. Shipped
- You have run Kubernetes in anger — and ideally built parts of it: operators, schedulers, controllers. You understand what happens underneath it, and you have worked on Linux directly, not just on managed services that sit on top of it
- You have run GPU workloads on Kubernetes, or you are confident you can own that domain fast
- You think like a developer who happens to build infrastructure, not an operator who manages it. You write code other engineers depend on
- Extensive experience building backend or infrastructure systems
- You have partnered with product, design, and business teams to ship software that reached real users
- A low-ego, team-first mindset. We care less about your exact domain and more about whether you are the kind of technical force other engineers want to work alongside
What the job involves
- Mistral is building a sovereign AI cloud for Europe. Our customers in finance, healthcare, and the public sector run frontier models on European-jurisdiction infrastructure, and the Cloud Platform team builds the systems that make that possible — compute orchestration, Kubernetes, bare metal, storage, networking, and the datacenter fleet that runs it all
- We run it all on our own metal, our own network, our own datacenters — which means when something breaks, the fix is ours to write
- European Compute Units let enterprises commit to multi-year capacity on that infrastructure, and we are scaling toward a gigawatt of compute across Europe by 2030. You will design and ship the layer every sovereign AI deployment depends on and shape the team building it
- This is a people-leadership role from day one
- You will manage the team — hiring, coaching, performance, growth paths, honest feedback — while staying close to the code: roughly half your time in architecture decisions and the hardest technical problems the team faces, the other half leading your squad
- If you are looking for a senior IC role, this is not it
- You will own our Kubernetes product end to end: a metal-to-on-demand platform built on in-house infrastructure, with GPU support for training, inference, and general-purpose compute
- Kubernetes is our product, not just our platform — we run it on infrastructure we own end to end
- You will decide how the control plane scales, how GPUs get scheduled, and how quickly a rack of bare metal becomes an on-demand cluster a customer can use
- The decisions you make here shape how our infrastructure scales from today's footprint to a gigawatt, and how we turn frontier AI research into production systems used by millions
- This is a role for an engineer who leads from the front because that is where the work is, not because management was the next rung on the ladder
- Design and ship the control plane. You build alongside your team and own the architecture and the hardest implementation decisions — scheduling, operators, provisioning, node lifecycle
- Grow the engineers, not just the software. You set the standard for ownership, remove the obstacles in their way, and coach them past their comfort zone until the work they ship surprises them
- Own the reliability of the Kubernetes control plane. It is the team's headline KPI. You make the calls when it breaks at 3am, and your engineers learn from how you do it
- Shrink the distance from metal to on-demand. Provisioning a cluster should be minutes of automation, not weeks of tickets
- Partner with Product Managers to set priorities, scope initiatives, and make the technical and business tradeoffs
- Own people management for the team: hiring, performance, growth paths, and honest feedback — the leadership work that never becomes someone else's job
- Define the team's processes and execution rituals as it grows
Salary benchmarks
Our take
Founded by Facebook AI researchers, Mistral AI focuses on developing open-source generative AI models to "make AI useful." It emerged in early 2023, quickly achieving a $260 million valuation.
Mistral features up to 176 billion parameters, and its open-source nature has sparked concerns about potential misuse. However, Mistral remains a formidable competitor in the AI landscape, challenging models from Google and Meta.
In 2025, Mistral secured a massive €1.7 billion funding round, raising its valuation to €11.7 billion. This Series B funding, led by European chip firm ASML, underscores significant interest in alternatives to ChatGPT and a push away from Silicon Valley dependence by European AI competitors.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 5 rounds)
Sep 2025
$1.9bn
SERIES C
Jun 2024
$532.5m
SERIES B
Total funding: $3.0bn
Company benefits
- Competitive bonus structure
- Equity
- Opportunities for professional growth and development
Company HQ
Villette, Paris, France
Leadership
Timothee Lacroix
(Co-Founder & CTO)Previously PhD and Software Engineer Intern at Facebook and Visiting Undergraduate at CAlab UCSD
Guillaume Lample
(Co-Founder & Chief Scientist)Research Student and Scientist at Facebook AI and Research Intern at Jane Street Capital
Arthur Mensch
(Co-Founder & CEO)Previously Staff Research Scientist at DeepMind, Post-doc researcher at École normale supérieure, Visiting Researcher at NYU Courant Institute of Mathematical Sciences and PhD Student at Inria
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